Publications
241.
Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius
Modelling spatial patterns of urban growth in Africa Journal Article
In: Applied Geography, vol. 44, pp. 23-32, 2013, ISSN: 0143-6228.
Abstract | Links | BibTeX | Tags: Africa, Boosted regression trees, Modelling, Spatial pattern, Urban growth
@article{LINARD201323,
title = {Modelling spatial patterns of urban growth in Africa},
author = {Catherine Linard and Andrew J. Tatem and Marius Gilbert},
url = {https://www.sciencedirect.com/science/article/pii/S0143622813001707},
doi = {https://doi.org/10.1016/j.apgeog.2013.07.009},
issn = {0143-6228},
year = {2013},
date = {2013-01-01},
journal = {Applied Geography},
volume = {44},
pages = {23-32},
abstract = {The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.},
keywords = {Africa, Boosted regression trees, Modelling, Spatial pattern, Urban growth},
pubstate = {published},
tppubtype = {article}
}
The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers.
242.
Metcalf, C. J. E.; Cohen, C.; Lessler, J.; McAnerney, J. M.; Ntshoe, G. M.; Puren, A.; Klepac, P.; Tatem, A.; Grenfell, B. T.; Bjørnstad, O. N.
Implications of spatially heterogeneous vaccination coverage for the risk of congenital rubella syndrome in South Africa Journal Article
In: Journal of The Royal Society Interface, vol. 10, no. 78, pp. 20120756, 2013.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1098/rsif.2012.0756,
title = {Implications of spatially heterogeneous vaccination coverage for the risk of congenital rubella syndrome in South Africa},
author = {C. J. E. Metcalf and C. Cohen and J. Lessler and J. M. McAnerney and G. M. Ntshoe and A. Puren and P. Klepac and A. Tatem and B. T. Grenfell and O. N. Bjørnstad},
url = {https://royalsocietypublishing.org/doi/abs/10.1098/rsif.2012.0756},
doi = {10.1098/rsif.2012.0756},
year = {2013},
date = {2013-01-01},
journal = {Journal of The Royal Society Interface},
volume = {10},
number = {78},
pages = {20120756},
abstract = {Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Since vaccination at levels short of those necessary to achieve eradication may increase the average age of infection, and thus potentially the CRS burden, introduction of the vaccine has been limited to contexts where coverage is high. Recent work suggests that spatial heterogeneity in coverage should also be a focus of concern. Here, we use a detailed dataset from South Africa to explore the implications of heterogeneous vaccination for the burden of CRS, introducing realistic vaccination scenarios based on reported levels of measles vaccine coverage. Our results highlight the potential impact of country-wide reductions of incidence of rubella on the local CRS burdens in districts with small population sizes. However, simulations indicate that if rubella vaccination is introduced with coverage reflecting current estimates for measles coverage in South Africa, the burden of CRS is likely to be reduced overall over a 30 year time horizon by a factor of 3, despite the fact that this coverage is lower than the traditional 80 per cent rule of thumb for vaccine introduction, probably owing to a combination of relatively low birth and transmission rates. We conclude by discussing the likely impact of private-sector vaccination.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Since vaccination at levels short of those necessary to achieve eradication may increase the average age of infection, and thus potentially the CRS burden, introduction of the vaccine has been limited to contexts where coverage is high. Recent work suggests that spatial heterogeneity in coverage should also be a focus of concern. Here, we use a detailed dataset from South Africa to explore the implications of heterogeneous vaccination for the burden of CRS, introducing realistic vaccination scenarios based on reported levels of measles vaccine coverage. Our results highlight the potential impact of country-wide reductions of incidence of rubella on the local CRS burdens in districts with small population sizes. However, simulations indicate that if rubella vaccination is introduced with coverage reflecting current estimates for measles coverage in South Africa, the burden of CRS is likely to be reduced overall over a 30 year time horizon by a factor of 3, despite the fact that this coverage is lower than the traditional 80 per cent rule of thumb for vaccine introduction, probably owing to a combination of relatively low birth and transmission rates. We conclude by discussing the likely impact of private-sector vaccination.
243.
Smith, David L.; Cohen, Justin M.; Chiyaka, Christinah; Johnston, Geoffrey; Gething, Peter W.; Gosling, Roly; Buckee, Caroline O.; Laxminarayan, Ramanan; Hay, Simon I.; Tatem, Andrew J.
A sticky situation: the unexpected stability of malaria elimination Journal Article
In: Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 368, no. 1623, pp. 20120145, 2013.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1098/rstb.2012.0145,
title = {A sticky situation: the unexpected stability of malaria elimination},
author = {David L. Smith and Justin M. Cohen and Christinah Chiyaka and Geoffrey Johnston and Peter W. Gething and Roly Gosling and Caroline O. Buckee and Ramanan Laxminarayan and Simon I. Hay and Andrew J. Tatem},
url = {https://royalsocietypublishing.org/doi/abs/10.1098/rstb.2012.0145},
doi = {10.1098/rstb.2012.0145},
year = {2013},
date = {2013-01-01},
journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},
volume = {368},
number = {1623},
pages = {20120145},
abstract = {Malaria eradication involves eliminating malaria from every country where transmission occurs. Current theory suggests that the post-elimination challenges of remaining malaria-free by stopping transmission from imported malaria will have onerous operational and financial requirements. Although resurgent malaria has occurred in a majority of countries that tried but failed to eliminate malaria, a review of resurgence in countries that successfully eliminated finds only four such failures out of 50 successful programmes. Data documenting malaria importation and onwards transmission in these countries suggests malaria transmission potential has declined by more than 50-fold (i.e. more than 98%) since before elimination. These outcomes suggest that elimination is a surprisingly stable state. Elimination's ‘stickiness’ must be explained either by eliminating countries starting off qualitatively different from non-eliminating countries or becoming different once elimination was achieved. Countries that successfully eliminated were wealthier and had lower baseline endemicity than those that were unsuccessful, but our analysis shows that those same variables were at best incomplete predictors of the patterns of resurgence. Stability is reinforced by the loss of immunity to disease and by the health system's increasing capacity to control malaria transmission after elimination through routine treatment of cases with antimalarial drugs supplemented by malaria outbreak control. Human travel patterns reinforce these patterns; as malaria recedes, fewer people carry malaria from remote endemic areas to remote areas where transmission potential remains high. Establishment of an international resource with backup capacity to control large outbreaks can make elimination stickier, increase the incentives for countries to eliminate, and ensure steady progress towards global eradication. Although available evidence supports malaria elimination's stickiness at moderate-to-low transmission in areas with well-developed health systems, it is not yet clear if such patterns will hold in all areas. The sticky endpoint changes the projected costs of maintaining elimination and makes it substantially more attractive for countries acting alone, and it makes spatially progressive elimination a sensible strategy for a malaria eradication endgame.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Malaria eradication involves eliminating malaria from every country where transmission occurs. Current theory suggests that the post-elimination challenges of remaining malaria-free by stopping transmission from imported malaria will have onerous operational and financial requirements. Although resurgent malaria has occurred in a majority of countries that tried but failed to eliminate malaria, a review of resurgence in countries that successfully eliminated finds only four such failures out of 50 successful programmes. Data documenting malaria importation and onwards transmission in these countries suggests malaria transmission potential has declined by more than 50-fold (i.e. more than 98%) since before elimination. These outcomes suggest that elimination is a surprisingly stable state. Elimination's ‘stickiness’ must be explained either by eliminating countries starting off qualitatively different from non-eliminating countries or becoming different once elimination was achieved. Countries that successfully eliminated were wealthier and had lower baseline endemicity than those that were unsuccessful, but our analysis shows that those same variables were at best incomplete predictors of the patterns of resurgence. Stability is reinforced by the loss of immunity to disease and by the health system's increasing capacity to control malaria transmission after elimination through routine treatment of cases with antimalarial drugs supplemented by malaria outbreak control. Human travel patterns reinforce these patterns; as malaria recedes, fewer people carry malaria from remote endemic areas to remote areas where transmission potential remains high. Establishment of an international resource with backup capacity to control large outbreaks can make elimination stickier, increase the incentives for countries to eliminate, and ensure steady progress towards global eradication. Although available evidence supports malaria elimination's stickiness at moderate-to-low transmission in areas with well-developed health systems, it is not yet clear if such patterns will hold in all areas. The sticky endpoint changes the projected costs of maintaining elimination and makes it substantially more attractive for countries acting alone, and it makes spatially progressive elimination a sensible strategy for a malaria eradication endgame.
244.
Qi, Qiuyin; Guerra, Carlos A.; Moyes, Catherine L.; Elyazar, Iqbal AR F.; Gething, Peter W.; Hay, Simon I.; Tatem, Andrew J.
The effects of urbanization on global Plasmodium vivax malaria transmission Journal Article
In: Malaria Journal, vol. 11, no. 1, pp. 403, 2012, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Qi2012,
title = {The effects of urbanization on global Plasmodium vivax malaria transmission},
author = {Qiuyin Qi and Carlos A. Guerra and Catherine L. Moyes and Iqbal AR F. Elyazar and Peter W. Gething and Simon I. Hay and Andrew J. Tatem},
url = {https://doi.org/10.1186/1475-2875-11-403},
doi = {10.1186/1475-2875-11-403},
issn = {1475-2875},
year = {2012},
date = {2012-12-05},
journal = {Malaria Journal},
volume = {11},
number = {1},
pages = {403},
abstract = {Many recent studies have examined the impact of urbanization on Plasmodium falciparum malaria endemicity and found a general trend of reduced transmission in urban areas. However, none has examined the effect of urbanization on Plasmodium vivax malaria, which is the most widely distributed malaria species and can also cause severe clinical syndromes in humans. In this study, a set of 10,003 community-based P. vivax parasite rate (Pv PR) surveys are used to explore the relationships between Pv PR in urban and rural settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many recent studies have examined the impact of urbanization on Plasmodium falciparum malaria endemicity and found a general trend of reduced transmission in urban areas. However, none has examined the effect of urbanization on Plasmodium vivax malaria, which is the most widely distributed malaria species and can also cause severe clinical syndromes in humans. In this study, a set of 10,003 community-based P. vivax parasite rate (Pv PR) surveys are used to explore the relationships between Pv PR in urban and rural settings.
245.
Pindolia, Deepa K.; Garcia, Andres J.; Wesolowski, Amy; Smith, David L.; Buckee, Caroline O.; Noor, Abdisalan M.; Snow, Robert W.; Tatem, Andrew J.
Human movement data for malaria control and elimination strategic planning Journal Article
In: Malaria Journal, vol. 11, no. 1, pp. 205, 2012, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Pindolia2012,
title = {Human movement data for malaria control and elimination strategic planning},
author = {Deepa K. Pindolia and Andres J. Garcia and Amy Wesolowski and David L. Smith and Caroline O. Buckee and Abdisalan M. Noor and Robert W. Snow and Andrew J. Tatem},
url = {https://doi.org/10.1186/1475-2875-11-205},
doi = {10.1186/1475-2875-11-205},
issn = {1475-2875},
year = {2012},
date = {2012-06-18},
journal = {Malaria Journal},
volume = {11},
number = {1},
pages = {205},
abstract = {Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.
246.
Tatem, Andrew J.; Adamo, Susana; Bharti, Nita; Burgert, Clara R.; Castro, Marcia; Dorelien, Audrey; Fink, Gunter; Linard, Catherine; John, Mendelsohn; Montana, Livia; Montgomery, Mark R.; Nelson, Andrew; Noor, Abdisalan M.; Pindolia, Deepa; Yetman, Greg; Balk, Deborah
Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation Journal Article
In: Population Health Metrics, vol. 10, no. 1, pp. 8, 2012, ISSN: 1478-7954.
Abstract | Links | BibTeX | Tags:
@article{Tatem2012,
title = {Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation},
author = {Andrew J. Tatem and Susana Adamo and Nita Bharti and Clara R. Burgert and Marcia Castro and Audrey Dorelien and Gunter Fink and Catherine Linard and Mendelsohn John and Livia Montana and Mark R. Montgomery and Andrew Nelson and Abdisalan M. Noor and Deepa Pindolia and Greg Yetman and Deborah Balk},
url = {https://doi.org/10.1186/1478-7954-10-8},
doi = {10.1186/1478-7954-10-8},
issn = {1478-7954},
year = {2012},
date = {2012-05-16},
journal = {Population Health Metrics},
volume = {10},
number = {1},
pages = {8},
abstract = {The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models.
247.
Linard, Catherine; Tatem, Andrew J.
Large-scale spatial population databases in infectious disease research Journal Article
In: International Journal of Health Geographics, vol. 11, no. 1, pp. 7, 2012, ISSN: 1476-072X.
Abstract | Links | BibTeX | Tags:
@article{Linard2012,
title = {Large-scale spatial population databases in infectious disease research},
author = {Catherine Linard and Andrew J. Tatem},
url = {https://doi.org/10.1186/1476-072X-11-7},
doi = {10.1186/1476-072X-11-7},
issn = {1476-072X},
year = {2012},
date = {2012-03-20},
journal = {International Journal of Health Geographics},
volume = {11},
number = {1},
pages = {7},
abstract = {Modelling studies on the spatial distribution and spread of infectious diseases are becoming increasingly detailed and sophisticated, with global risk mapping and epidemic modelling studies now popular. Yet, in deriving populations at risk of disease estimates, these spatial models must rely on existing global and regional datasets on population distribution, which are often based on outdated and coarse resolution data. Moreover, a variety of different methods have been used to model population distribution at large spatial scales. In this review we describe the main global gridded population datasets that are freely available for health researchers and compare their construction methods, and highlight the uncertainties inherent in these population datasets. We review their application in past studies on disease risk and dynamics, and discuss how the choice of dataset can affect results. Moreover, we highlight how the lack of contemporary, detailed and reliable data on human population distribution in low income countries is proving a barrier to obtaining accurate large-scale estimates of population at risk and constructing reliable models of disease spread, and suggest research directions required to further reduce these barriers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Modelling studies on the spatial distribution and spread of infectious diseases are becoming increasingly detailed and sophisticated, with global risk mapping and epidemic modelling studies now popular. Yet, in deriving populations at risk of disease estimates, these spatial models must rely on existing global and regional datasets on population distribution, which are often based on outdated and coarse resolution data. Moreover, a variety of different methods have been used to model population distribution at large spatial scales. In this review we describe the main global gridded population datasets that are freely available for health researchers and compare their construction methods, and highlight the uncertainties inherent in these population datasets. We review their application in past studies on disease risk and dynamics, and discuss how the choice of dataset can affect results. Moreover, we highlight how the lack of contemporary, detailed and reliable data on human population distribution in low income countries is proving a barrier to obtaining accurate large-scale estimates of population at risk and constructing reliable models of disease spread, and suggest research directions required to further reduce these barriers.
248.
Cohen, Justin M.; Woolsey, Aaron M.; Sabot, Oliver J.; Gething, Peter W.; Tatem, Andrew J.; Moonen, Bruno
Optimizing Investments in Malaria Treatment and Diagnosis Journal Article
In: Science, vol. 338, no. 6107, pp. 612-614, 2012.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1126/science.1229045,
title = {Optimizing Investments in Malaria Treatment and Diagnosis},
author = {Justin M. Cohen and Aaron M. Woolsey and Oliver J. Sabot and Peter W. Gething and Andrew J. Tatem and Bruno Moonen},
url = {https://www.science.org/doi/abs/10.1126/science.1229045},
doi = {10.1126/science.1229045},
year = {2012},
date = {2012-01-01},
journal = {Science},
volume = {338},
number = {6107},
pages = {612-614},
abstract = {Better targeting of antimalarials to people who need them will maximize the impact of interventions in the private sector. The Roll Back Malaria (RBM) Partnership has set an ambitious target of achieving near zero deaths from malaria by 2015 (1). Scale-up of insecticide-treated nets, indoor residual spraying of insecticide, and increased access to treatment with artemisinin-based combination therapies (ACTs) over the past decade have led to reductions in malaria incidence of more than 50% in 43 countries, including 8 in Africa (2). However, as an estimated 655,000 malaria deaths still occurred in 2010 (2), with the great majority in sub-Saharan Africa, substantial challenges remain.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Better targeting of antimalarials to people who need them will maximize the impact of interventions in the private sector. The Roll Back Malaria (RBM) Partnership has set an ambitious target of achieving near zero deaths from malaria by 2015 (1). Scale-up of insecticide-treated nets, indoor residual spraying of insecticide, and increased access to treatment with artemisinin-based combination therapies (ACTs) over the past decade have led to reductions in malaria incidence of more than 50% in 43 countries, including 8 in Africa (2). However, as an estimated 655,000 malaria deaths still occurred in 2010 (2), with the great majority in sub-Saharan Africa, substantial challenges remain.
249.
Wesolowski, Amy; Eagle, Nathan; Tatem, Andrew J.; Smith, David L.; Noor, Abdisalan M.; Snow, Robert W.; Buckee, Caroline O.
Quantifying the Impact of Human Mobility on Malaria Journal Article
In: Science, vol. 338, no. 6104, pp. 267-270, 2012.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1126/science.1223467,
title = {Quantifying the Impact of Human Mobility on Malaria},
author = {Amy Wesolowski and Nathan Eagle and Andrew J. Tatem and David L. Smith and Abdisalan M. Noor and Robert W. Snow and Caroline O. Buckee},
url = {https://www.science.org/doi/abs/10.1126/science.1223467},
doi = {10.1126/science.1223467},
year = {2012},
date = {2012-01-01},
journal = {Science},
volume = {338},
number = {6104},
pages = {267-270},
abstract = {An obstacle to developing effective national malaria control programs is a lack of understanding of human movements, which are an important component of disease transmission. As mobile phones have become increasingly ubiquitous, it is now possible to collect individual-level, longitudinal data on human movements on a massive scale. Wesolowski et al. (p. 267) analyzed mobile phone call data records representing the travel patterns of 15 million mobile phone owners in Kenya over the course of a year. This was combined with a detailed malaria risk map, to estimate malaria parasite movements across the country that could be caused by human movement. This information enabled detailed analysis of parasite sources and sinks between hundreds of local settlements. Estimates were compared with hospital data from Nairobi to show that local pockets of transmission likely occur around the periphery of Nairobi, accounting for locally acquired cases, contrary to the accepted idea that there is no transmission in the capital. Geographical information in mobile phone records for 15 million Kenyans is linked to malaria prevalence estimates. Human movements contribute to the transmission of malaria on spatial scales that exceed the limits of mosquito dispersal. Identifying the sources and sinks of imported infections due to human travel and locating high-risk sites of parasite importation could greatly improve malaria control programs. Here, we use spatially explicit mobile phone data and malaria prevalence information from Kenya to identify the dynamics of human carriers that drive parasite importation between regions. Our analysis identifies importation routes that contribute to malaria epidemiology on regional spatial scales.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
An obstacle to developing effective national malaria control programs is a lack of understanding of human movements, which are an important component of disease transmission. As mobile phones have become increasingly ubiquitous, it is now possible to collect individual-level, longitudinal data on human movements on a massive scale. Wesolowski et al. (p. 267) analyzed mobile phone call data records representing the travel patterns of 15 million mobile phone owners in Kenya over the course of a year. This was combined with a detailed malaria risk map, to estimate malaria parasite movements across the country that could be caused by human movement. This information enabled detailed analysis of parasite sources and sinks between hundreds of local settlements. Estimates were compared with hospital data from Nairobi to show that local pockets of transmission likely occur around the periphery of Nairobi, accounting for locally acquired cases, contrary to the accepted idea that there is no transmission in the capital. Geographical information in mobile phone records for 15 million Kenyans is linked to malaria prevalence estimates. Human movements contribute to the transmission of malaria on spatial scales that exceed the limits of mosquito dispersal. Identifying the sources and sinks of imported infections due to human travel and locating high-risk sites of parasite importation could greatly improve malaria control programs. Here, we use spatially explicit mobile phone data and malaria prevalence information from Kenya to identify the dynamics of human carriers that drive parasite importation between regions. Our analysis identifies importation routes that contribute to malaria epidemiology on regional spatial scales.
250.
Linard, Catherine; Gilbert, Marius; Snow, Robert W.; Noor, Abdisalan M.; Tatem, Andrew J.
Population Distribution, Settlement Patterns and Accessibility across Africa in 2010 Journal Article
In: PLOS ONE, vol. 7, no. 2, pp. 1-8, 2012.
Abstract | Links | BibTeX | Tags:
@article{10.1371/journal.pone.0031743,
title = {Population Distribution, Settlement Patterns and Accessibility across Africa in 2010},
author = {Catherine Linard and Marius Gilbert and Robert W. Snow and Abdisalan M. Noor and Andrew J. Tatem},
url = {https://doi.org/10.1371/journal.pone.0031743},
doi = {10.1371/journal.pone.0031743},
year = {2012},
date = {2012-01-01},
journal = {PLOS ONE},
volume = {7},
number = {2},
pages = {1-8},
publisher = {Public Library of Science},
abstract = {The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accurately measure population concentration and accessibility. Here we outline approaches to developing a new high resolution population distribution dataset for Africa and analyse rural accessibility to population centers. Contemporary population count data were combined with detailed satellite-derived settlement extents to map population distributions across Africa at a finer spatial resolution than ever before. Substantial heterogeneity in settlement patterns, population concentration and spatial accessibility to major population centres is exhibited across the continent. In Africa, 90% of the population is concentrated in less than 21% of the land surface and the average per-person travel time to settlements of more than 50,000 inhabitants is around 3.5 hours, with Central and East Africa displaying the longest average travel times. The analyses highlight large inequities in access, the isolation of many rural populations and the challenges that exist between countries and regions in providing access to services. The datasets presented are freely available as part of the AfriPop project, providing an evidence base for guiding strategic decisions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The spatial distribution of populations and settlements across a country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accurately measure population concentration and accessibility. Here we outline approaches to developing a new high resolution population distribution dataset for Africa and analyse rural accessibility to population centers. Contemporary population count data were combined with detailed satellite-derived settlement extents to map population distributions across Africa at a finer spatial resolution than ever before. Substantial heterogeneity in settlement patterns, population concentration and spatial accessibility to major population centres is exhibited across the continent. In Africa, 90% of the population is concentrated in less than 21% of the land surface and the average per-person travel time to settlements of more than 50,000 inhabitants is around 3.5 hours, with Central and East Africa displaying the longest average travel times. The analyses highlight large inequities in access, the isolation of many rural populations and the challenges that exist between countries and regions in providing access to services. The datasets presented are freely available as part of the AfriPop project, providing an evidence base for guiding strategic decisions.
251.
Linard, Catherine; Gilbert, Marius; Tatem, Andrew J.
Assessing the use of global land cover data for guiding large area population distribution modelling Journal Article
In: GeoJournal, vol. 76, no. 5, pp. 525-538, 2011, ISSN: 1572-9893.
Abstract | Links | BibTeX | Tags:
@article{Linard2011,
title = {Assessing the use of global land cover data for guiding large area population distribution modelling},
author = {Catherine Linard and Marius Gilbert and Andrew J. Tatem},
url = {https://doi.org/10.1007/s10708-010-9364-8},
doi = {10.1007/s10708-010-9364-8},
issn = {1572-9893},
year = {2011},
date = {2011-10-01},
journal = {GeoJournal},
volume = {76},
number = {5},
pages = {525-538},
abstract = {Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover data, thus restricting application of the approach to this region. If gridded population data are to be improved across Africa, an alternative, consistent and comparable source of land cover data is required. Here these analyses were repeated for Kenya using four continent-wide land cover datasets combined with detailed settlement extents and accuracies were assessed against detailed census data. The aim was to identify the large area land cover dataset that, combined with detailed settlement extents, produce the most accurate population distribution data. The effectiveness of the population distribution modelling procedures in the absence of high resolution census data was evaluated, as was the extrapolation ability of population densities between different regions. Results showed that the use of the GlobCover dataset refined with detailed settlement extents provided significantly more accurate gridded population data compared to the use of refined AVHRR-derived, MODIS-derived and GLC2000 land cover datasets. This study supports the hypothesis that land cover information is important for improving population distribution model accuracies, particularly in countries where only coarse resolution census data are available. Obtaining high resolution census data must however remain the priority. With its higher spatial resolution and its more recent data acquisition, the GlobCover dataset was found as the most valuable resource to use in combination with detailed settlement extents for the production of gridded population datasets across large areas.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover data, thus restricting application of the approach to this region. If gridded population data are to be improved across Africa, an alternative, consistent and comparable source of land cover data is required. Here these analyses were repeated for Kenya using four continent-wide land cover datasets combined with detailed settlement extents and accuracies were assessed against detailed census data. The aim was to identify the large area land cover dataset that, combined with detailed settlement extents, produce the most accurate population distribution data. The effectiveness of the population distribution modelling procedures in the absence of high resolution census data was evaluated, as was the extrapolation ability of population densities between different regions. Results showed that the use of the GlobCover dataset refined with detailed settlement extents provided significantly more accurate gridded population data compared to the use of refined AVHRR-derived, MODIS-derived and GLC2000 land cover datasets. This study supports the hypothesis that land cover information is important for improving population distribution model accuracies, particularly in countries where only coarse resolution census data are available. Obtaining high resolution census data must however remain the priority. With its higher spatial resolution and its more recent data acquisition, the GlobCover dataset was found as the most valuable resource to use in combination with detailed settlement extents for the production of gridded population datasets across large areas.
252.
Tatem, Andrew; Linard, Catherine
Population mapping of poor countries Journal Article
In: Nature, vol. 474, no. 7349, pp. 36-36, 2011, ISSN: 1476-4687.
@article{Tatem2011b,
title = {Population mapping of poor countries},
author = {Andrew Tatem and Catherine Linard},
url = {https://doi.org/10.1038/474036d},
doi = {10.1038/474036d},
issn = {1476-4687},
year = {2011},
date = {2011-06-01},
journal = {Nature},
volume = {474},
number = {7349},
pages = {36-36},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
253.
Tatem, Andrew J.; Campiz, Nicholas; Gething, Peter W.; Snow, Robert W.; Linard, Catherine
The effects of spatial population dataset choice on estimates of population at risk of disease Journal Article
In: Population Health Metrics, vol. 9, no. 1, pp. 4, 2011, ISSN: 1478-7954.
Abstract | Links | BibTeX | Tags:
@article{Tatem2011,
title = {The effects of spatial population dataset choice on estimates of population at risk of disease},
author = {Andrew J. Tatem and Nicholas Campiz and Peter W. Gething and Robert W. Snow and Catherine Linard},
url = {https://doi.org/10.1186/1478-7954-9-4},
doi = {10.1186/1478-7954-9-4},
issn = {1478-7954},
year = {2011},
date = {2011-02-07},
journal = {Population Health Metrics},
volume = {9},
number = {1},
pages = {4},
abstract = {The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.
254.
Linard, Catherine; Alegana, Victor A.; Noor, Abdisalan M.; Snow, Robert W.; Tatem, Andrew J.
A high resolution spatial population database of Somalia for disease risk mapping Journal Article
In: International Journal of Health Geographics, vol. 9, no. 1, pp. 45, 2010, ISSN: 1476-072X.
Abstract | Links | BibTeX | Tags:
@article{Linard2010,
title = {A high resolution spatial population database of Somalia for disease risk mapping},
author = {Catherine Linard and Victor A. Alegana and Abdisalan M. Noor and Robert W. Snow and Andrew J. Tatem},
url = {https://doi.org/10.1186/1476-072X-9-45},
doi = {10.1186/1476-072X-9-45},
issn = {1476-072X},
year = {2010},
date = {2010-09-14},
journal = {International Journal of Health Geographics},
volume = {9},
number = {1},
pages = {45},
abstract = {Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data.
255.
Tatem, Andrew J.; Smith, David L.
International population movements and regional Plasmodium falciparum malaria elimination strategies Journal Article
In: Proceedings of the National Academy of Sciences, vol. 107, no. 27, pp. 12222-12227, 2010.
Abstract | Links | BibTeX | Tags:
@article{doi:10.1073/pnas.1002971107,
title = {International population movements and regional \textit{Plasmodium falciparum} malaria elimination strategies},
author = {Andrew J. Tatem and David L. Smith},
url = {https://www.pnas.org/doi/abs/10.1073/pnas.1002971107},
doi = {10.1073/pnas.1002971107},
year = {2010},
date = {2010-01-01},
journal = {Proceedings of the National Academy of Sciences},
volume = {107},
number = {27},
pages = {12222-12227},
abstract = {Calls for the eradication of malaria require the development of global and regional strategies based on a strong and consistent evidence base. Evidence from the previous global malaria eradication program and more recent transborder control campaigns have shown the importance of accounting for human movement in introducing infections to areas targeted for elimination. Here, census-based migration data were analyzed with network analysis tools, Plasmodium falciparum malaria transmission maps, and global population databases to map globally communities of countries linked by relatively high levels of infection movements. The likely principal sources and destinations of imported cases in each region were also mapped. Results indicate that certain groups of countries, such as those in West Africa and central Asia are much more strongly connected by relatively high levels of population and infection movement than others. In contrast, countries such as Ethiopia and Myanmar display significantly greater isolation in terms of likely infection movements in and out. The mapping here of both communities of countries linked by likely higher levels of infection movement, and “natural” migration boundaries that display reduced movement of people and infections between regions has practical utility. These maps can inform the design of malaria elimination strategies by identifying regional communities of countries afforded protection from recolonization by surrounding regions of reduced migration. For more isolated countries, a nationally focused control or elimination program is likely to stand a better chance of success than those receiving high levels of visitors and migrants from high-transmission regions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Calls for the eradication of malaria require the development of global and regional strategies based on a strong and consistent evidence base. Evidence from the previous global malaria eradication program and more recent transborder control campaigns have shown the importance of accounting for human movement in introducing infections to areas targeted for elimination. Here, census-based migration data were analyzed with network analysis tools, Plasmodium falciparum malaria transmission maps, and global population databases to map globally communities of countries linked by relatively high levels of infection movements. The likely principal sources and destinations of imported cases in each region were also mapped. Results indicate that certain groups of countries, such as those in West Africa and central Asia are much more strongly connected by relatively high levels of population and infection movement than others. In contrast, countries such as Ethiopia and Myanmar display significantly greater isolation in terms of likely infection movements in and out. The mapping here of both communities of countries linked by likely higher levels of infection movement, and “natural” migration boundaries that display reduced movement of people and infections between regions has practical utility. These maps can inform the design of malaria elimination strategies by identifying regional communities of countries afforded protection from recolonization by surrounding regions of reduced migration. For more isolated countries, a nationally focused control or elimination program is likely to stand a better chance of success than those receiving high levels of visitors and migrants from high-transmission regions.
256.
Tatem, Andrew J.; Guerra, Carlos A.; Kabaria, Caroline W.; Noor, Abdisalan M.; Hay, Simon I.
Human population, urban settlement patterns and their impact on Plasmodium falciparum malaria endemicity Journal Article
In: Malaria Journal, vol. 7, no. 1, pp. 218, 2008, ISSN: 1475-2875.
Abstract | Links | BibTeX | Tags:
@article{Tatem2008,
title = {Human population, urban settlement patterns and their impact on Plasmodium falciparum malaria endemicity},
author = {Andrew J. Tatem and Carlos A. Guerra and Caroline W. Kabaria and Abdisalan M. Noor and Simon I. Hay},
url = {https://doi.org/10.1186/1475-2875-7-218},
doi = {10.1186/1475-2875-7-218},
issn = {1475-2875},
year = {2008},
date = {2008-10-27},
journal = {Malaria Journal},
volume = {7},
number = {1},
pages = {218},
abstract = {The efficient allocation of financial resources for malaria control and the optimal distribution of appropriate interventions require accurate information on the geographic distribution of malaria risk and of the human populations it affects. Low population densities in rural areas and high population densities in urban areas can influence malaria transmission substantially. Here, the Malaria Atlas Project (MAP) global database of Plasmodium falciparum parasite rate (Pf PR) surveys, medical intelligence and contemporary population surfaces are utilized to explore these relationships and other issues involved in combining malaria risk maps with those of human population distribution in order to define populations at risk more accurately.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The efficient allocation of financial resources for malaria control and the optimal distribution of appropriate interventions require accurate information on the geographic distribution of malaria risk and of the human populations it affects. Low population densities in rural areas and high population densities in urban areas can influence malaria transmission substantially. Here, the Malaria Atlas Project (MAP) global database of Plasmodium falciparum parasite rate (Pf PR) surveys, medical intelligence and contemporary population surfaces are utilized to explore these relationships and other issues involved in combining malaria risk maps with those of human population distribution in order to define populations at risk more accurately.
257.
Tatem, Andrew J.; Noor, Abdisalan M.; Hagen, Craig; Gregorio, Antonio Di; Hay, Simon I.
High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa Journal Article
In: PLOS ONE, vol. 2, no. 12, pp. 1-8, 2007.
Abstract | Links | BibTeX | Tags:
@article{10.1371/journal.pone.0001298,
title = {High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa},
author = {Andrew J. Tatem and Abdisalan M. Noor and Craig Hagen and Antonio Di Gregorio and Simon I. Hay},
url = {https://doi.org/10.1371/journal.pone.0001298},
doi = {10.1371/journal.pone.0001298},
year = {2007},
date = {2007-01-01},
journal = {PLOS ONE},
volume = {2},
number = {12},
pages = {1-8},
publisher = {Public Library of Science},
abstract = {BackgroundBetween 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.Methodology/Principal FindingsWe examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.ConclusionsWe find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BackgroundBetween 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.Methodology/Principal FindingsWe examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.ConclusionsWe find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available.
258.
Hay, S. I.; Noor, A. M.; Nelson, A.; Tatem, A. J.
The accuracy of human population maps for public health application Journal Article
In: Tropical Medicine & International Health, vol. 10, no. 10, pp. 1073-1086, 2005.
Abstract | Links | BibTeX | Tags: areal weighting, census, dasymetric mapping, demography, Kenya, pycnophylactic interpolation, smart interpolation
@article{https://doi.org/10.1111/j.1365-3156.2005.01487.x,
title = {The accuracy of human population maps for public health application},
author = {S. I. Hay and A. M. Noor and A. Nelson and A. J. Tatem},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-3156.2005.01487.x},
doi = {https://doi.org/10.1111/j.1365-3156.2005.01487.x},
year = {2005},
date = {2005-01-01},
journal = {Tropical Medicine & International Health},
volume = {10},
number = {10},
pages = {1073-1086},
abstract = {Summary Objectives Human population totals are used for generating burden of disease estimates at global, continental and national scales to help guide priority setting in international health financing. These exercises should be aware of the accuracy of the demographic information used. Methods The analysis presented in this paper tests the accuracy of five large-area, public-domain human population distribution data maps against high spatial resolution population census data enumerated in Kenya in 1999. We illustrate the epidemiological significance, by assessing the impact of using these different human population surfaces in determining populations at risk of various levels of climate suitability for malaria transmission. We also describe how areal weighting, pycnophylactic interpolation and accessibility potential interpolation techniques can be used to generate novel human population distribution surfaces from local census information and evaluate to what accuracy this can be achieved. Results We demonstrate which human population distribution surface performed best and which population interpolation techniques generated the most accurate bespoke distributions. Despite various levels of modelling complexity, the accuracy achieved by the different surfaces was primarily determined by the spatial resolution of the input population data. The simplest technique of areal weighting performed best. Conclusions Differences in estimates of populations at risk of malaria in Kenya of over 1 million persons can be generated by the choice of surface, highlighting the importance of these considerations in deriving per capita health metrics in public health. Despite focussing on Kenya the results of these analyses have general application and are discussed in this wider context.},
keywords = {areal weighting, census, dasymetric mapping, demography, Kenya, pycnophylactic interpolation, smart interpolation},
pubstate = {published},
tppubtype = {article}
}
Summary Objectives Human population totals are used for generating burden of disease estimates at global, continental and national scales to help guide priority setting in international health financing. These exercises should be aware of the accuracy of the demographic information used. Methods The analysis presented in this paper tests the accuracy of five large-area, public-domain human population distribution data maps against high spatial resolution population census data enumerated in Kenya in 1999. We illustrate the epidemiological significance, by assessing the impact of using these different human population surfaces in determining populations at risk of various levels of climate suitability for malaria transmission. We also describe how areal weighting, pycnophylactic interpolation and accessibility potential interpolation techniques can be used to generate novel human population distribution surfaces from local census information and evaluate to what accuracy this can be achieved. Results We demonstrate which human population distribution surface performed best and which population interpolation techniques generated the most accurate bespoke distributions. Despite various levels of modelling complexity, the accuracy achieved by the different surfaces was primarily determined by the spatial resolution of the input population data. The simplest technique of areal weighting performed best. Conclusions Differences in estimates of populations at risk of malaria in Kenya of over 1 million persons can be generated by the choice of surface, highlighting the importance of these considerations in deriving per capita health metrics in public health. Despite focussing on Kenya the results of these analyses have general application and are discussed in this wider context.
259.
Tatem, A. J.; Noor, A. M.; Hay, S. I.
Assessing the accuracy of satellite derived global and national urban maps in Kenya Journal Article
In: Remote Sensing of Environment, vol. 96, no. 1, pp. 87-97, 2005, ISSN: 0034-4257.
Abstract | Links | BibTeX | Tags: Accuracy assessment, Urban area mapping, Urbanization
@article{TATEM200587,
title = {Assessing the accuracy of satellite derived global and national urban maps in Kenya},
author = {A. J. Tatem and A. M. Noor and S. I. Hay},
url = {https://www.sciencedirect.com/science/article/pii/S0034425705000702},
doi = {https://doi.org/10.1016/j.rse.2005.02.001},
issn = {0034-4257},
year = {2005},
date = {2005-01-01},
journal = {Remote Sensing of Environment},
volume = {96},
number = {1},
pages = {87-97},
abstract = {Ninety percent of projected global urbanization will be concentrated in low income countries. This will have considerable environmental, economic and public health implications for those populations. Objective and efficient methods of delineating urban extent are a cross-sectoral need complicated by a diversity of urban definition rubrics world-wide. Large-area maps of urban extents are becoming increasingly available in the public domain, as are a wide-range of medium spatial resolution satellite imagery. Here we describe the extension of a methodology based on Landsat ETM and Radarsat imagery to the production of a human settlement map of Kenya. This map was then compared with five satellite imagery-derived, global maps of urban extent at Kenya national-level, against an expert opinion coverage for accuracy assessment. The results showed the map produced using medium spatial resolution satellite imagery was of comparable accuracy to the expert opinion coverage. The five global urban maps exhibited a range of inaccuracies, emphasising that care should be taken with use of these maps at national and sub-national scale.},
keywords = {Accuracy assessment, Urban area mapping, Urbanization},
pubstate = {published},
tppubtype = {article}
}
Ninety percent of projected global urbanization will be concentrated in low income countries. This will have considerable environmental, economic and public health implications for those populations. Objective and efficient methods of delineating urban extent are a cross-sectoral need complicated by a diversity of urban definition rubrics world-wide. Large-area maps of urban extents are becoming increasingly available in the public domain, as are a wide-range of medium spatial resolution satellite imagery. Here we describe the extension of a methodology based on Landsat ETM and Radarsat imagery to the production of a human settlement map of Kenya. This map was then compared with five satellite imagery-derived, global maps of urban extent at Kenya national-level, against an expert opinion coverage for accuracy assessment. The results showed the map produced using medium spatial resolution satellite imagery was of comparable accuracy to the expert opinion coverage. The five global urban maps exhibited a range of inaccuracies, emphasising that care should be taken with use of these maps at national and sub-national scale.
260.
Tatem, A. J.; Hay, S. I.
Measuring urbanization pattern and extent for malaria research: A review of remote sensing approaches Journal Article
In: Journal of Urban Health, vol. 81, no. 3, pp. 363-376, 2004, ISSN: 1468-2869.
Abstract | Links | BibTeX | Tags:
@article{Tatem2004,
title = {Measuring urbanization pattern and extent for malaria research: A review of remote sensing approaches},
author = {A. J. Tatem and S. I. Hay},
url = {https://doi.org/10.1093/jurban/jth124},
doi = {10.1093/jurban/jth124},
issn = {1468-2869},
year = {2004},
date = {2004-09-01},
journal = {Journal of Urban Health},
volume = {81},
number = {3},
pages = {363-376},
abstract = {Within the next 30 years, the proportion of urban dwellers will rise from under half to two thirds of the world's population. Such a shift will entail massive public health consequences, and most of this urban transition will occur in low-income regions of the world. Urban populations face very different health risks compared to those in rural areas, particularly in terms of malaria. To target effective and relevant public health interventions, the need for clear, consistent definitions of what determines urban areas and urban communities is paramount. Decision makers are increasingly seeing remote sensing as a cost-effective solution to monitoring urbanization at a range of spatial scales. This review focuses on the progress made within the field of remote sensing on mapping, monitoring, and modeling urban environments and examines existing challenges, drawbacks, and future prospects. We conclude by exploring' some of the particular relevance of these issues to malaria and note that they are of more general relevance to all those interested in urban public health.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Within the next 30 years, the proportion of urban dwellers will rise from under half to two thirds of the world's population. Such a shift will entail massive public health consequences, and most of this urban transition will occur in low-income regions of the world. Urban populations face very different health risks compared to those in rural areas, particularly in terms of malaria. To target effective and relevant public health interventions, the need for clear, consistent definitions of what determines urban areas and urban communities is paramount. Decision makers are increasingly seeing remote sensing as a cost-effective solution to monitoring urbanization at a range of spatial scales. This review focuses on the progress made within the field of remote sensing on mapping, monitoring, and modeling urban environments and examines existing challenges, drawbacks, and future prospects. We conclude by exploring' some of the particular relevance of these issues to malaria and note that they are of more general relevance to all those interested in urban public health.
